Triple

T20337394
Position Surface form Disambiguated ID Type / Status
Subject Frances Russell, Countess Russell E495649 entity
Predicate familyName P18 FINISHED
Object Russell NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Russell | Statement: [Frances Russell, Countess Russell, familyName, Russell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russell
Context triple: [Frances Russell, Countess Russell, familyName, Russell]
  • A. Russell chosen
    Russell is a common English surname most famously associated with legendary Boston Celtics basketball player and civil rights activist Bill Russell.
  • B. Russell
    Russell is the enthusiastic young Wilderness Explorer who befriends elderly widower Carl Fredricksen in Pixar's animated film "Up."
  • C. Russell
    Russell is a sharp-tongued, wisecracking young member of the Junkyard Gang in the animated series "Fat Albert and the Cosby Kids."
  • D. Russell
    Russell is a rural municipality in eastern Ontario, Canada, known for its bilingual (English and French) community and proximity to Ottawa.
  • E. Russell
    Russell is the middle name of Rensselaer Russell Nelson, an American jurist who served as a United States federal judge in the 19th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4a1a09881908d97270d6971a25a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677ed75e081909bfc534033ac1c59 completed April 20, 2026, 7:01 p.m.
Created at: April 16, 2026, 11:23 a.m.